Microscopic Image Depth of Field Extension via Energy Matrix Alignment
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Solution Overview
Problem
Conventional imaging devices face challenges in achieving an extended depth of field due to limitations in existing digital image processing techniques, which often result in misalignment, illumination variations, noise, low image quality, and high computational complexity, especially when dealing with large image stacks.
Innovation Solution
A method and system for constructing a composite image with extended depth of field by aligning multiple images using a bi-directional image alignment process, performing illumination and color correction, generating energy matrices, and creating depth maps to combine focused regions from multiple images, thereby reducing processing time and memory requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multiple images are captured to form an image stack to extend depth of field, then the depth of field in the composite image is improved, but the processing time and computational complexity increase
Solution Approach 1:
The patent divides the image stack processing into multiple stages: initial alignment, coarse depth estimation, refinement processing, and composite generation. This segmentation allows processing to be performed in manageable steps rather than all at once, reducing overall processing time while maintaining depth of field quality.
Solution Approach 2:
The patent performs preliminary alignment and coarse depth estimation before detailed processing. By pre-processing the image stack to establish basic relationships and eliminate obvious misalignments, the subsequent detailed processing requires less computational effort and time.
2Manufacturing precision
If multiple images are captured to form an image stack to extend depth of field, then the depth of field in the composite image is improved, but the memory requirement increases
Solution Approach 1:
The patent extracts only the essential depth information from the image stack through coarse depth estimation, rather than processing all image data in full detail. This extraction approach maintains the depth of field effect while significantly reducing memory requirements by working with condensed depth maps rather than full-resolution image stacks.
Solution Approach 2:
The patent performs preliminary processing to create compressed representations of the image stack, extracting key depth and alignment information before detailed composite generation. This preliminary compression reduces memory requirements while preserving the essential information needed for high-quality depth of field extension.
3Manufacturing precision
If conventional digital image processing techniques are used to combine images, then the depth of field is extended, but misalignment and illumination variations occur
Solution Approach 1:
The patent implements an iterative refinement process where alignment and depth estimation are repeatedly improved based on feedback from previous processing stages. Each refinement cycle uses the results of the previous cycle to correct misalignments and reduce illumination variations, progressively improving image quality and reliability.
Solution Approach 2:
The patent uses dynamic adjustment of alignment parameters and processing strategies based on the specific characteristics of the image stack. Rather than applying fixed processing steps, the system adapts its processing approach to the actual content and quality of the input images, improving alignment accuracy and reducing artifacts.
Data Source
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AI summary
The invention relates to an image processing method and system for constructing composite image with extended depth of field. The composite image may be constructed from a plurality of source images of a scene stored in an image stack. The method includes aligning the images in the image stack such that every image in the image stack is aligned with other images in the stack, performing illumination and color correction on the aligned images in the image stack, generating an energy matrix for each pixel of each illumination and color corrected image in the image stack by computing energy content for each pixel, generating a raw index map that contains the location of every pixels having maximum energy level among all the images in the image stack, generating degree of defocus ma and constructing the composite image.